A novel, integrated smoke simulation design method supporting local projection and guiding control over adaptive grids

  • Authors:

  • Qing Zuo;Yue Qi;Hong Qin

  • Affiliations:

  • State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China;State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China;Computer Science Department, Stony Brook University, Stony Brook, USA 11790

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics
  • Year:
  • 2013

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Abstract

High-fidelity smoke simulation in a large-scale complex environment is extremely time-consuming due to the expensive computational cost of using highly dense regular grids. There have been quite a few improved algorithms/techniques aiming to enhance the simulation's visual effects and reduce the time consumption during the last two decades. However, most of the state-of-the-art methods will encounter difficulties of not being able to model fine turbulent details during simulation or losing high-frequency shape details at the fine scale when simulated smoke interacting with nearby obstacles. One straightforward solution is to continue to refine spatial resolution at the expense of increased time complexity. This paper, however, advocates an improved strategy for smoke simulation design over adaptive grids, while simultaneously enabling the functionalities of local projection and guiding control. First, our new integrated method supports adaptive grid projection that can significantly reduce the computational cost during the velocity projection phase. During smoke simulation design, the use of adaptive grids flexibly accommodates finer cells near obstacles with fine details, and coarser cells anywhere else, as a result, fine-scale object features can be faithfully retained without the need of global grid refinement. Second, our integrated solution over adaptive grids can tightly couple guiding control with local projection, which is capable of handling tiny obstacles that are impossible to model with global coarse grids alone during simulation preview. Comprehensive experiments have shown that our integrated method has the advantage of generating turbulent phenomena when interacting with small-scale features of obstacles, and at the same time offering the preview mechanism for efficient large-scale smoke simulation design.